카노와 의사결정나무를 활용한 금융서비스 로봇의 품질속성 분석 : 은행지점 도입용 금융서비스 로봇 사례

Abstract

A Kano model was used to classify the quality attributes of the service robot function for actual deployment that can support and replace bank employees. Quality attributes for a total of 6 dimensions and 23 service elements were divided into bank employees and customer groups, and service priorities were derived after comparative analysis. The Decision tree model was used to supplement the excessive simplification of quality attributes by the modest number of Kano models and to classify and predict by segment market. Of the 23 services, 16 were classified into the same attributes in both groups. 6 services classified as combination attributes used a Decision tree to identify differences in perception of quality attributes among groups. In terms of basic financial services and professional financial services, it was confirmed that bank employees feel financial service robots more attractive than ordinary customers. In the design of IT convergence service, we propose a methodology for deriving quality attributes by combining a Kano model for classifying quality attributes of two groups and a Decision tree for forecasting subdivision markets.